Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
31 measurements spanning 38 days, net +2,091. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 13,828–16,547 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 31
Measured (UTC)
Subscribers
Change
15 Sept 2026, 00:18
16,233
+119
13 Sept 2026, 10:58
16,114
+113
11 Sept 2026, 11:15
16,001
+189
8 Sept 2026, 14:39
15,812
+170
5 Sept 2026, 10:20
15,642
+82
3 Sept 2026, 16:00
15,560
+14
2 Sept 2026, 10:03
15,546
+51
1 Sept 2026, 06:28
15,495
+47
31 Aug 2026, 03:27
15,448
+43
30 Aug 2026, 06:26
15,405
+50
29 Aug 2026, 07:56
15,355
+51
28 Aug 2026, 09:03
15,304
+46
27 Aug 2026, 10:55
15,258
+94
26 Aug 2026, 07:32
15,164
+61
25 Aug 2026, 08:57
15,103
+79
24 Aug 2026, 05:26
15,024
+111
22 Aug 2026, 10:35
14,913
+35
20 Aug 2026, 23:34
14,878
+53
19 Aug 2026, 20:13
14,825
+56
18 Aug 2026, 23:25
14,769
first reading
Engagement
18 posts held, back to 11 May 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 51 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
24.3%
avg views ÷ 16,233 subscribers
Avg views / post
3,950
2 posts measured
Reaction rate
1.38%
reactions ÷ views · ER floor
Posts in window
2
of 18 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 2 September 2026
Posts held
18 (11 May 2026 – 2 September 2026)
Views total
7,890
Reactions total
109
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 10:45 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
1m 36s
Average length
24s
Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
1,702 reactions across 18 posts, in 27 distinct kinds. The most used accounts for 56.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
954
56.1%
❤
413
24.3%
👍
125
7.34%
🌚
60
3.53%
❤🔥
39
2.29%
👾
16
0.94%
⚡
13
0.764%
🆒
13
0.764%
🤗
10
0.588%
💘
9
0.529%
🗿
9
0.529%
😁
7
0.411%
👌
5
0.294%
🤩
4
0.235%
👨💻
3
0.176%
🙉
3
0.176%
🤝
3
0.176%
🫡
3
0.176%
😘
2
0.118%
😭
2
0.118%
7 further kinds
9
0.529%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 18 of the 18 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,702 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 11 May 2026 to 2 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
16
across the posts below
Posts paid on
4
of 18 we hold a reading for · 22%
Most on one post
7
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @TifofeyMontage. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 18 most recent posts we hold for this entry, published 11 May 2026 to 2 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Подборка стильных роликов [для вдохновения] 🍸
Сейчас монтирую новый ролик про ошибки в монтаже. И в нём как раз затрагиваю тему насмотренности и стиля
Для монтажёра очень важно не только знать разные эффекты и приёмы монтажа, но и уметь собрать из всего этого единую картинку в одном стиле
Так монтаж начинает выглядеть дороже и сильнее цепляет зрителя
Поэтому я частенько сохраняю в соцсетях понравившиеся по стилю …
Вай, какой монтаж ❤️🔥
Недавно ученик курса по монтажу Захар поделился своими работами в чате
И мне они прям очень понравились!
Такой аккуратный, минималистичный монтаж. Всё на своих местах, ничего лишнего
Именно то, что сейчас нужно блогерам в Instagram, TikTok и других соцсетях
Причём Захар попал на обучение буквально месяц назад с минимальными навыками монтажа. И за это время уже научился делать такие работы.…
Возвращаюсь в блог ☀️
Давно не было постов в канале, вот исправляюсь :)
Последний месяц выдался по-настоящему летним
Я успел:
- Накупаться в карьере
- Побывать в древних
городах
- Покататься на дрезине
- Построить туалет и хозблок на даче
- Ну и просто позагорать на пляже
И отдохнул, и руками поработал, а теперь снова возвращаюсь в рабочий ритм 👨💻
Буду готовить для вас новые ролики и полезные материалы)
А как …
🎥 Моё оборудование для съёмки YouTube-видео
Как и обещал в ролике, оставляю ссылки на всё оборудование, которым пользуюсь сам
Не обязательно покупать именно эти модели, но если хотите собрать похожий сетап без долгих поисков - этот список сэкономит вам много времени
📸 Штативы
1. Основной штатив (1,8 м)
Удобный вариант для дома и съёмок в поездках
https://ozon.ru/t/hiw1hq4
2. Magic Arm
Использую для крепления кам…
Научу тебя СНИМАТЬ ВИДЕО на смартфон, как ПРОФИ за 16 минут 😎
Ура! Наконец-то доделал этот ролик, много сил вложил в его создание. Думаю получилось действительно полезно)
В видео рассказал, как качественно снимать на смартфон:
от выбора локации и построения кадра до настроек камеры, света и других мелочей, которые сильно влияют на итоговую картинку
Видео будет полезно всем, кто хоть раз что-то снимал на смартфон, …
📚 Что почитать летом начинающим фрилансерам (монтажёрам)?
Последнее время часто читаю книги по саморазвитию, бизнесу и фрилансу
Конечно, художественную литературу читать интереснее, но вот знания из неё не всегда можно сразу применить.
А с прикладными книгами всё иначе: прочитал главу про работу с клиентами и уже на следующий день затестил новый приём в переписке. По-моему топ!
Вот подборка книг, которые могу смел…
Планирую сделать ролик о том, как записывать видео на ютюб
Разберу с нуля:
- Как правильно настроить камеру / iPhone
- Как выставить свет
- Какой микрофон выбрать
- Какие настройки
использовать
- И какое оборудование стоит покупать, а на что не тратить деньги
Думаю будет супер полезный видос для начинающих
Как вам такая идея?
🔥 - топ, будем смотреть
🌚 - лучше ролик про монтаж
Весь CapCut за 1 час 🤯
Если вы давно хотели научиться монтировать на ПК, но не знали с чего начать — это видео для вас
В новом ролике я разобрал все основные инструменты CapCut на ПК и на практике показал процесс монтажа «интро» для своего видео
Туториал без воды, только самое полезное
Записывал это видео более 5-ти часов
Во время съемки камера перегревалась 3 раза, свет разряжался.
И на монтаже столкнулся с 200+…
Вы видели цены на компы? ☠️
Недавно виделся с младшим братом, Фёдором
И он рассказал, что купил себе новый мощный компьютер за 160 000 ₽ 🤑
Для тех, кто не знает: прошлым летом Федя прошёл мое обучение по монтажу.
Собрал небольшое портфолио, нашел первых клиентов и начал монтировать рилсы на заказ
Днём он ходил в школу, а вечером монтировал по 1–2 ролика
Постепенно откладывал деньги с заказов и в итоге накопил на…
❤80🔥42👾10👍8🤝1
Showing the 12 most recent of 18 posts we hold for @TifofeyMontage. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
The shares total 117%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 18 most recent posts we hold, published 11 May 2026 to 2 September 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 15 September 2026 — this
entry's latest reading, not the date you are reading this.
“Tifofey | Монтаж” (@TifofeyMontage), 16,233 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/TifofeyMontage.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.